Encoding and decoding systems and methods for MPEG and other block-based video bit-stream data are now widely known. The fundamentals are well summarized in U.S. Pat. No. 6,870,883 (“Iwata”), incorporated herein by this reference. Iwata discloses a three-processor system and method for video encoding and decoding, to achieve a modicum of parallelism and improved performance over a strictly sequential solution. the interdependency of bits or blocks of the video frame. It is also difficult to maximize the performance by keeping all processors as busy as possible due to differing requirements of the processors.
One property of video is that for any given block of pixels (e.g. macroblock) in the video frame, there is a high correlation to neighboring blocks. Video compression technologies take advantage of this through the use of prediction. When the video is encoded, the encoder predicts block properties based on neighboring blocks and then encodes the difference (residual) from the prediction. The video decoder computes the same prediction and adds the residual to the prediction to decompress the video. Since only residuals to the predictions are sent, the amount of information sent between the encoder and the decoder is compressed. One drawback to having block properties predicted based off neighboring blocks is that if a neighboring block contains an error, for example due to interference during a broadcast, then all subsequent blocks will also contain an error causing an entire frame of video to be corrupted. For this reason, these video compression standards contain a notion of a slice.
A “slice” of video data contains a set of blocks that can be decoded without any other neighboring block information (from outside the slice). At each slice, the predictors are reset, trading off compression efficiency for error resilience. The majority of encoded MPEG2 content, for example, uses one slice per line of blocks. If an error is introduced in any given block, the system can recover on the next line of blocks.
Two other properties of video that allow it to be compressed are these: high frequency information can be discarded without the human vision system detecting a noticeable change in the results; and, motion tends to be localized to certain areas of the picture. Video compression standards take advantage of these two properties by a method called quantization and motion estimation/motion compensation, respectively.
Finally, to further compress the video data, a lossless variable length encoding scheme is used in video compression technologies. These methods may even use a context adaptive algorithm causing further dependency on data previously encoded or decoded in the data stream.
Some known solutions utilize multiple sequential processors or arrays of processors connected by a network such as Ethernet or high speed memory interface. These solutions suffer in efficiency from insufficient number of processors, and memory bandwidth/latency in sending data to all the processors.
Other proposals for parallelizing video decoding and encoding have been proposed such as that disclosed in U.S. Pat. No. 6,870,883 which describes a system for decoding video using multiple processors. That system requires the computationally expensive ability to transfer data to and from processors at each macroblock.
The need remains for improvements in methods and systems for video data processing to improve throughput while maintaining video quality and controlling costs.